Sea-land transition phase shale gas reservoir multi-scale fracture characterization method and device

Abstract

The invention relates to the technical field of oil exploration reservoir prediction, and discloses a sea-land transition phase shale gas reservoir multi-scale fracture characterization method and device, and the method comprises the steps: carrying out the calculation of seismic imaging data through employing a multi-dip angle variance volume technology, and obtaining large-scale fracture data; calculating the seismic imaging data by using an ant body technology to obtain mesoscale crack data; performing strong reflection removal on the seismic imaging data to obtain weak signal seismic data; performing root mean square amplitude calculation on the weak signal seismic data to obtain small-scale crack data; and performing multi-resolution fusion on the large-scale fracture data, the medium-scale fracture data and the small-scale fracture data to obtain multi-scale fracture representation information of the sea-land transition phase shale gas reservoir. According to the method, the problem that a single fracture prediction method is difficult to comprehensively describe fracture distribution is solved, the infection of coal seam strong reflection shielding is eliminated, and the distribution condition of sea-land transition phase stratum fractures is systematically predicted.

Description

Technical Field

[0001] This invention relates to the field of oil exploration reservoir prediction technology, and in particular to a method and apparatus for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs. Background Technology

[0002] In recent years, shale gas has played an increasingly important role in the energy sector, with significant progress made in the exploration of shale gas in the transitional marine-onshore facies, demonstrating the enormous potential for shale gas exploration and development in my country. Compared to other countries, my country's shale gas exploration started relatively late, and its exploration technologies are still under development and not yet mature. Currently, a large number of seismic technologies have been applied in China, such as the preliminary success of seismic geometric attribute prediction of faults. Seismic attribute detection technology has been widely used in fault detection. Compared with the variance volume algorithm, curvature attributes have a better ability to identify geological features such as deflection, folds, and uplifts in seismic data. Seismic dip and azimuth attributes are well-suited for identifying mesoscale faults that are difficult to identify using variance volume techniques. Seismic variance attributes calculate the variance between seismic traces and mean traces, highlighting faults and anomalous geological bodies through variance volumes, thus complementing and developing variance volume techniques.

[0003] As predictive research deepens, the domestic industry has recognized the need to further improve the accuracy of reservoir fracture prediction. While existing technologies can predict fractures to some extent, fracture detection methods based on seismic attribute analysis are primarily designed for tectonic-scale geological features, and their detection resolution is limited.

[0004] This invention employs variance volume to identify large-scale faults, utilizes ant-body attributes to characterize the spatial distribution of mesoscale fractures, and predicts small-scale fracture information based on diffraction signal extraction and attribute analysis techniques. Furthermore, it uses a fusion technique of three different scale fractures to characterize the effective fracture information in concentrated shale gas thickness sections, providing technical support for the identification of shale gas sweet spots and the selection of favorable target areas. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs, thereby addressing the shortcomings of existing seismic attribute analysis techniques in multi-scale fracture detection. To achieve the above objective, this invention provides the following technical solution:

[0006] This invention provides a method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs, the method comprising:

[0007] Large-scale crack data were obtained by using multi-tilt variance volume technology to calculate seismic imaging data;

[0008] The ant body technique was used to calculate the seismic imaging data to obtain mesoscale crack data;

[0009] Strong reflections are removed from seismic imaging data to obtain weak signal seismic data; root mean square amplitude is calculated from the weak signal seismic data to obtain small-scale crack data.

[0010] The large-scale fracture data, the medium-scale fracture data, and the small-scale fracture data are fused at multiple resolutions to obtain multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs.

[0011] Furthermore, the process of using multi-dip variance volume technology to process seismic imaging data to obtain large-scale crack data includes:

[0012] Plane wave destruction filtering is applied to the seismic imaging data to obtain the dip angles in two directions, the main survey line and the connecting line, forming a dip surface;

[0013] A windowed data volume is formed by adding windows along the inclined plane;

[0014] Multi-angle variance volume calculation is performed on the windowed data volume to obtain large-scale crack data.

[0015] Furthermore, the variance volume of the windowed data volume is calculated to obtain large-scale crack data, including:

[0016] Using the multi-tilt variance volume technique, the average amplitude of the corresponding sample points within the time window length of each seismic trace involved in the calculation in the windowed data volume is calculated, as well as the variance volume value of the amplitude value of each sample point within the time window length and the average amplitude value of the seismic traces involved in the calculation at the same time.

[0017] When the variance volume value reaches the threshold, the variance volume value is large-scale crack data.

[0018] Furthermore, the formula for calculating the multi-angle variance volume is:

[0019]

[0020] x is the variance volume value. ij Let be the earthquake amplitude value of the i-th trace at time j; Let be the average amplitude value of all seismic traces at time j, L be the time window length of the variance, I be the adjacent traces used to calculate the variance value at a certain point, t be the time of the calculation point, and w be the mean amplitude value of all seismic traces at time j. j-t Let be the triangular weight function within time jt, and the sum of the weighted functions is... l is the index of the triangular weight function w.

[0021] Furthermore, the process of removing strong reflections from seismic imaging data to obtain weak signal seismic data includes:

[0022] The diffracted waves are separated from the seismic imaging data using a plane wave destruction filter;

[0023] The diffracted wave is subjected to strong reflection removal to obtain weak signal seismic data, which is shielded by strong reflection.

[0024] Furthermore, the strong reflection removal of the diffracted wave includes:

[0025] Dip angle estimation is performed on seismic imaging data, and median filtering is applied along the dip angle to obtain smoothed data.

[0026] Subtracting slip data from seismic imaging data yields weak-signal seismic data.

[0027] Furthermore, the large-scale crack data, the medium-scale crack data, and the small-scale crack data are fused at multiple resolutions, including:

[0028] Based on the large-scale fracture data, the mesoscale fracture data, and the small-scale fracture data, extract the large-scale fracture along-layer data, the mesoscale fracture along-layer data, and the small-scale fracture along-layer data along the seismic interpretation target layer;

[0029] Based on the large-scale fracture along-layer data, the medium-scale fracture along-layer data, and the small-scale fracture along-layer data, large-scale fracture along-layer images, medium-scale fracture along-layer images, and small-scale fracture along-layer images are obtained.

[0030] Gaussian images were obtained by performing Gaussian blur downsampling on large-scale, medium-scale, and small-scale crack along-layer images respectively.

[0031] The Gaussian image is calculated to obtain different layers of the Gaussian image;

[0032] The results of different layers of the Gaussian image are weighted and summed to obtain the multi-scale fracture characterization results of the marine-continental transitional shale gas reservoir.

[0033] Furthermore, the seismic imaging data is seismic imaging data with residual noise removed.

[0034] The present invention also provides a multi-scale fracture characterization device for marine-continental transitional shale gas reservoirs, the device comprising,

[0035] The first unit is used to process seismic imaging data using multi-tilt variance volume technology to obtain large-scale crack data.

[0036] The second unit is used to process seismic imaging data using ant body technology to obtain mesoscale crack data.

[0037] The third unit is used to remove strong reflections from the seismic imaging data to obtain weak signal seismic data; and to calculate the root mean square amplitude of the weak signal seismic data to obtain the small-scale crack data.

[0038] The fourth unit is used to perform multi-resolution fusion of the large-scale fracture data, the medium-scale fracture data, and the small-scale fracture data to obtain multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs.

[0039] The present invention also provides an electronic device, the electronic device comprising at least one processor and at least one memory, the memory being data-connected to the processor, wherein,

[0040] The memory stores instructions executable by the at least one processor, which, when executed, enable the at least one processor to perform the described method. Technical effects and advantages of the present invention:

[0041] This invention addresses the challenges of complex lithofacies assemblages, frequent lithological variations, large fracture scale variations, high seismic data frequency variations, low signal-to-noise ratios, and strong coal seam reflection shielding in transitional marine-continental strata. It employs and integrates sensitive prediction methods for large, medium, and small fractures, respectively, overcoming the difficulty of comprehensively characterizing fracture distribution using a single fracture prediction method. This eliminates the interference of strong coal seam reflection shielding and systematically predicts the fracture distribution in transitional marine-continental strata.

[0042] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0043] Figure 1a This is a flowchart of the multi-scale fracture characterization method for marine-continental transitional shale gas reservoirs according to the present invention;

[0044] Figure 1b This is a flowchart illustrating the implementation of the multi-scale fracture characterization method for marine-continental transitional shale gas reservoirs in a specific embodiment of the present invention.

[0045] Figure 2 This is a schematic diagram of a large-scale crack in the test area using the multi-angle coherent variance volume technique in a specific embodiment of the present invention.

[0046] Figure 3 This is a schematic diagram of cracks in the ant body in the test area of ​​a specific embodiment of the present invention;

[0047] Figure 4This is a diagram showing the root mean square diffraction properties of the test area in a specific embodiment of the present invention.

[0048] Figure 5 This is a diagram showing the multi-scale crack fusion effect in the test area of ​​a specific embodiment of the present invention;

[0049] Figure 6 This is a block diagram of the electronic device structure in a specific embodiment of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] To address the shortcomings of existing technologies, this invention discloses a multi-scale fracture characterization method for marine-continental transitional shale gas reservoirs, such as... Figure 1a As shown, the method includes,

[0052] Step 1: Calculate large-scale crack data from seismic imaging data using multi-dip variance volume technology;

[0053] Step 2: Calculate the seismic imaging data using the ant body technique to obtain mesoscale crack data;

[0054] Step 3: Remove strong reflections from the seismic imaging data to obtain weak signal seismic data; calculate the root mean square amplitude of the weak signal seismic data to obtain the small-scale crack data;

[0055] Step 4: Perform multi-resolution fusion of the large-scale fracture data, the medium-scale fracture data, and the small-scale fracture data to obtain multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs.

[0056] In one specific embodiment of the present invention, the seismic imaging data is preprocessed and noise-removed seismic imaging data. The beneficial effects are: preprocessing the obtained seismic imaging data and removing residual noise reduces the impact of noise on the effective waves, which is beneficial for the analysis of diffracted waves to obtain high-resolution diffractors.

[0057] In a specific embodiment of the present invention, step 1: calculating large-scale crack data from seismic imaging data using multi-dip variance volume technology includes:

[0058] Step 101: Perform plane wave destruction filtering on the seismic imaging data to obtain the dip angles in two directions, the main survey line and the connecting line, and form a dip surface;

[0059] Step 102: Add windows along the inclined plane to form a windowed data volume;

[0060] Step 103: Calculate the variance volume of the windowed data volume to obtain large-scale crack data, specifically:

[0061] Using the multi-dip coherent variance volume technique, the average amplitude of the corresponding samples within the time window length of each seismic trace involved in the calculation, and the variance between the amplitude value of each sample within the time window and the average amplitude of the seismic traces involved in the calculation, are calculated to obtain large-scale crack data. The multi-dip coherent variance volume calculation formula is as follows:

[0062]

[0063] x is the variance volume value. ij Let be the earthquake amplitude value of the i-th trace at time j; Let be the average amplitude value of all seismic traces at time j, L be the time window length of the variance, I be the adjacent traces used to calculate the variance value at a certain point, t be the time of the calculation point, and w be the mean amplitude value of all seismic traces at time j. j-t Let be the triangular weight function within time jt, and the sum of the weighted functions is... l is the index of the triangular weight function w.

[0064] In a specific embodiment of the present invention, for step 2: using the ant body technique to process the seismic imaging data, the crack characterization of a single ant body is not obvious. Therefore, multiple ant body tracking is performed on the ant body results to suppress false cracks and clearly characterize the cracks to obtain mesoscale crack data.

[0065] In a specific embodiment of the present invention, step 3: removing strong reflections from the seismic imaging data to obtain weak signal seismic data; calculating the root mean square amplitude of the weak signal seismic data to obtain the small-scale crack data; specifically:

[0066] Step 301: The step of removing strong reflections from seismic imaging data to obtain weak signal seismic data includes:

[0067] Step 302: Separate the diffracted waves from the seismic imaging data using a plane wave destruction filter; including the following steps:

[0068] Describing reflected wave signals using plane wave destruction filters: Linearized reflected waves in seismic imaging data can be described using plane wave destruction filters.

[0069] Q=C(p)S (1)

[0070] Where Q is the error term, and S = [S1, S2, ... SN ] T For seismic imaging data, p = [p1, p2, ..., p N-1 ] represents the slope of the phase axis, N represents the number of channels in the seismic imaging data, and C(p) represents the plane wave destruction operator.

[0071]

[0072] Where I is the identity matrix, C N-l，N (p N-l ) represents the plane wave destruction filter used to predict the Nth seismic imaging data from the (N-1)th seismic imaging data, C i,i+1 (p i ) represents the plane wave destruction filter used to predict the (i+1)th seismic imaging data from the i-th seismic imaging data, where i = 1, 2, ..., N-1;

[0073] P i Let represent the slope of the i-th in-phase axis. Its scalar form is:

[0074]

[0075] Among them, Z t Z x These represent the Z-transforms in the time and space directions, respectively.

[0076] To obtain the in-phase axis slope p of the seismic imaging data, we approximate the error term Q to be 0, and then define the following least-squares objective:

[0077] 0≈C(p)S (4)

[0078] The slope p of the phase axis of the seismic imaging data is obtained by solving equation (4) using the conjugate gradient method.

[0079] Step 303: Perform strong reflection removal on the diffracted wave to obtain weak signal seismic data. The weak signal seismic data is shielded by strong reflection. The strong reflection removal of the diffracted wave includes:

[0080] Step 3031: Estimate the dip angle of the seismic imaging data, perform median filtering along the dip angle, and obtain smoothed data;

[0081] Step 3032: Subtract the slip data from the seismic imaging data to obtain weak signal seismic data;

[0082] By utilizing plane wave destruction filters and the in-phase axis slope p of seismic imaging data, seismic reflection wave prediction imaging data of adjacent channels can be obtained from any seismic wave imaging data. For example, based on the seismic wave imaging data S of the i-th channel... i The predicted imaging data R of the seismic reflection wave of the (i+n)th channel is obtained. i+n,i :

[0083] R i+n,i =S i C i,i+1 C i+1,i+2 C i+2,i+3 …C i+k-1,i+k (5)

[0084] Based on the i-th seismic wave imaging data S i Obtain the predicted imaging data R of the in-th seismic reflection wave. i-n,i :

[0085] R i-n,i =S i C i-1,i C i-2,i-1 C i-3,i-2 …C i-n-1,i-n (6)

[0086] For each seismic imaging data track, we use the i-th seismic imaging data track as a template to predict the n adjacent data tracks to its left and right, ultimately obtaining 2n seismic reflection wave prediction imaging data tracks.

[0087]

[0088] The key parameter n should be an integer between 2 and 10.

[0089] The median filtering method is used to enhance the continuity of the predicted imaging data of seismic reflection waves, and the data is then superimposed to obtain the i-th seismic reflection wave imaging data R. i :

[0090]

[0091] Where median(·) represents median filtering, and stack(·) represents stacking along the direction of the predicted imaging data channel of the seismic reflection wave.

[0092] Finally, seismic diffraction wave imaging data is obtained by subtracting seismic reflection wave imaging data from seismic imaging data:

[0093] D = SR (9)

[0094] Where D represents seismic diffraction imaging data, and R = [R1, R2, ... R N ] T This is reflected wave imaging data.

[0095] In a specific embodiment of the present invention, step 4: performing multi-resolution fusion of the large-scale crack data, the medium-scale crack data, and the small-scale crack data includes:

[0096] Step 401: Based on the large-scale fracture data, the mesoscale fracture data, and the small-scale fracture data, extract the large-scale fracture along-layer data, the mesoscale fracture along-layer data, and the small-scale fracture along-layer data along the seismic interpretation target layer;

[0097] Step 402: Based on the large-scale fracture along-layer data, the mesoscale fracture along-layer data, and the small-scale fracture along-layer data, obtain the large-scale fracture along-layer image A, the mesoscale fracture along-layer image B, and the small-scale fracture along-layer image C;

[0098] Step 403: Perform Gaussian blur downsampling calculation on the large-scale crack along-layer image A, the medium-scale crack along-layer image B, and the small-scale crack along-layer image C to obtain the corresponding Gaussian images;

[0099] Step 404: Calculate the Gaussian image to obtain the results of different layers of the Gaussian image;

[0100] Step 405: Perform a weighted summation on the different layer results of the Gaussian image to obtain the multi-scale fracture characterization results of the marine-continental transitional shale gas reservoir.

[0101] In a specific embodiment of the present invention, steps 404 and 405 are specifically as follows:

[0102] 1) Gaussian blur downsampling is performed on the large-scale crack along-layer image A to obtain three images: A1, A2, and A3. A1 is set as DA1, A2 minus A1 is DA2, and A3 minus A2 is DA3. The same operation is performed on the medium-scale crack along-layer image B and the small-scale crack along-layer image C to obtain the results DB1, DB2, DB3 and DC1, DC2, DC3.

[0103] 2) For DA1, DB1, and DC1, an n×n neighborhood is selected in each image, where n is the window size. The gradient mean is calculated as GA1, GB1, and GC1, centered on each pixel. The largest of the three is taken as the value of the current pixel, resulting in the first layer result F1. The same gradient calculation and maximum value are performed for DA2, DB2, and DC2 images, as well as DA3, DB3, and DC3, to obtain the second layer result F2 and the third layer result F3, respectively.

[0104] 3) For the first layer result F1, the second layer result F2, and the third layer result F3, use the weight matrix to perform weighted summation to obtain the multi-scale fracture characterization results of the marine-continental transitional shale gas reservoir.

[0105] The present invention also provides a multi-scale fracture characterization device for marine-continental transitional shale gas reservoirs, the device comprising,

[0106] The first unit is used to process seismic imaging data using multi-tilt variance volume technology to obtain large-scale crack data.

[0107] The second unit is used to process seismic imaging data using ant body technology to obtain mesoscale crack data.

[0108] The third unit is used to remove strong reflections from the seismic imaging data to obtain weak signal seismic data; and to calculate the root mean square amplitude of the weak signal seismic data to obtain the small-scale crack data.

[0109] The fourth unit is used to perform multi-resolution fusion of the large-scale fracture data, the medium-scale fracture data, and the small-scale fracture data to obtain multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs.

[0110] Regarding the apparatus in the above embodiments, the specific manner in which each unit performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0111] The technical solution of the present invention will be further described below with reference to specific embodiments.

[0112] This invention provides a multi-scale fracture characterization technique for marine-continental transitional shale gas reservoirs, the process of which is as follows: Figure 1b It includes the following steps:

[0113] 1) Acquire seismic imaging data. Seismic imaging data is the raw seismic imaging data that has been processed, including preprocessing and removing residual noise.

[0114] Its beneficial effects are: preprocessing the obtained raw seismic imaging data and eliminating residual noise, reducing the impact of noise on effective waves, which is beneficial for the analysis of diffracted waves and obtaining high-resolution diffractors.

[0115] Attribute analysis is performed on the raw seismic imaging data. Based on the results of the attribute analysis, sensitive prediction methods suitable for acquiring large, medium, and small crack data are selected. Multi-dip variance volume technology is used to calculate adjacent traces of reflected seismic data, highlighting the multi-dip dissimilarity between adjacent traces to obtain large-scale crack data, such as... Figure 2 ,according to Figure 2 The results show that variance volume properties can effectively predict the distribution of large cracks. By using variance volume technology, the variance value of sample points is calculated by utilizing the correlation of seismic signals between adjacent traces of seismic imaging data, and discontinuity information in the data volume is extracted to predict large-scale cracks in the study area.

[0116] 2) Using the ant body technique, the seismic imaging data is processed to obtain mesoscale crack data, such as... Figure 3 As shown, according to Figure 3 The results show that the ant body technology can effectively predict the distribution of medium-sized cracks. By simulating the principle of ant colonies searching for food, electronic ants are deployed at equal intervals in the seismic body to identify discontinuous features, enhance crack information, predict mesoscale cracks, and repeat the prediction to strengthen the crack results.

[0117] 3) Use a PWD filter to eliminate strong reflected waves from the coal seam, extract the diffracted waves, calculate the root mean square amplitude of the diffracted waves, and predict small cracks that are shielded by strong coal seam reflections, such as... Figure 4 As shown, according to Figure 4 The results show that the root mean square of diffraction can effectively predict the distribution of large and small cracks; by removing strong reflections from the seismic imaging data, weak signal seismic data is obtained, and the root mean square amplitude of the weak signal seismic data is calculated to obtain the small-scale crack data.

[0118] 4) The variance volume, ant volume, and root mean square amplitude data are fused to form a multi-scale fracture prediction result for the marine-continental transition facies system that has removed the strong coal seam shielding, such as... Figure 5 As shown, along the target layer of seismic interpretation, the large-scale fracture data, the mesoscale fracture data, and the small-scale fracture data along the layer are extracted to obtain large-scale fracture along the layer image A, mesoscale fracture along the layer image B, and small-scale fracture along the layer image C; and multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs is obtained through a multi-resolution fusion method.

[0119] Its beneficial effects are as follows: Considering that existing conventional seismic attribute analysis methods cannot effectively characterize multi-scale fracture information in marine-continental transitional shale gas reservoirs, this invention first utilizes multi-dip variance volume technology to calculate adjacent reflection seismic traces, highlighting the multi-dip dissimilarity between adjacent traces and predicting large-scale fractures in shale gas reservoirs; secondly, it uses ant-body technology to identify faults and mesoscale fractures; thirdly, based on imaging data diffraction signal extraction and attribute analysis technology, it predicts small-scale fracture information within marine-continental transitional shale gas reservoirs; finally, through the fusion technology of three different scale fractures, it characterizes the effective fracture information in concentrated shale gas thickness sections, which is of positive significance for identifying effective reservoirs and guiding shale gas exploration and development.

[0120] Furthermore, the multi-dip coherent variance volume technique is characterized by performing plane wave destruction filtering on the seismic imaging data to obtain the dip angles in two directions, the main survey line and the connecting line, forming a dip surface; then, a windowed data volume is formed by adding windows along the dip surface, and the coherent variance volume is calculated on the windowed data volume to obtain large-scale crack data.

[0121] Furthermore, the strong reflection removal method estimates the dip angle of the seismic imaging data, performs median filtering along this dip angle to obtain smoothed data; the smoothed data is then subtracted from the seismic imaging data to obtain weak signal seismic data.

[0122] Furthermore, the multi-resolution fusion method described above performs Gaussian blur downsampling on fracture-along images at different scales, takes a neighborhood in each image, calculates the gradient mean, takes the largest value as the value of the current pixel, and performs weighted summation on different layers to obtain the multi-scale fracture characterization results of marine-continental transitional shale gas reservoirs.

[0123] This invention addresses the challenges of fracture prediction in transitional marine-continental shale reservoirs, including low seismic data resolution, large fracture scale variations, and the difficulty in predicting reflected seismic responses due to strong coal seam reflection shielding small fractures.

[0124] Dip-guided median filtering overcomes the limitations of traditional median filtering, which fails to identify and adapt to changes in strata dip angle due to its driving direction along the seismic grid. It effectively improves the signal-to-noise ratio without sacrificing the original seismic signal resolution. The marine-continental transition facies can form complex combinations of lithologies such as coal seams, sandstone, mudstone, and shale, with relatively thin single layers, significant lithological variations, and strong lateral heterogeneity. Seismic data is significantly affected by noise, exhibiting poor continuity of phase axes and indistinct fault boundaries. Applying dip-guided median filtering to post-stack seismic data makes the phase axes clearer and more continuous, and the fault boundaries more distinct.

[0125] Secondly, by fracturing the sensitive properties of fracts at different scales, we can obtain the multi-scale fracturing characteristics of the marine-continental transition facies.

[0126] Due to the complex lithofacies assemblage, frequent lithological variations, large frequency variations and low resolution of seismic data in marine-continental transitional shale gas reservoirs, coupled with strong reflection shielding from coal seams, single-attribute prediction methods cannot systematically and accurately characterize fractures. This paper calculates variance volume, ant volume, and diffraction wave amplitude for marine-continental transitional shale gas reservoirs with strong coal seam reflection shielding, predicts large, medium, and small-scale fractures separately, and then fuses the prediction results. The specific steps are as follows:

[0127] This invention targets the characteristics of marine-continental transitional shale formations. By fusing variance volume, ant volume, and root mean square amplitude of diffraction, it performs three-dimensional multi-scale fracture prediction for marine-continental transitional shale gas reservoirs containing strong coal seam reflection shielding. This eliminates the shielding effect of strong coal seam reflection waves, systematically predicts the distribution of multi-scale fractures, and effectively improves the prediction quality. It is of great significance for the study of sedimentary structures and exploration and development of marine-continental transitional shale gas reservoirs.

[0128] Based on the above disclosure, this disclosure also provides an electronic device. For example... Figure 6 As shown, the electronic device of this disclosure includes at least one processor electrically connected to the present invention and at least one memory electrically connected to the processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method steps as described above by the controller.

[0129] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs, characterized in that, The method includes, Large-scale crack data were obtained by using multi-tilt variance volume technology to calculate seismic imaging data; The ant body technique was used to calculate the seismic imaging data to obtain mesoscale crack data; Strong reflections are removed from seismic imaging data to obtain weak signal seismic data; The root mean square amplitude of the weak signal seismic data was calculated to obtain small-scale crack data; The large-scale fracture data, the medium-scale fracture data, and the small-scale fracture data are fused at multiple resolutions to obtain multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs.

2. The method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs according to claim 1, characterized in that, The process of processing seismic imaging data using multi-dip variance volume technology to obtain large-scale crack data includes: Plane wave destruction filtering is applied to the seismic imaging data to obtain the dip angles in two directions, the main survey line and the connecting line, forming a dip surface; A windowed data volume is formed by adding windows along the inclined plane; Multi-angle variance volume calculation is performed on the windowed data volume to obtain large-scale crack data.

3. The method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs according to claim 2, characterized in that, The variance volume of the windowed data volume is calculated to obtain large-scale crack data, including: Using the multi-tilt variance volume technique, the average amplitude of the corresponding sample points within the time window length of each seismic trace involved in the calculation in the windowed data volume is calculated, as well as the variance volume value of the amplitude value of each sample point within the time window length and the average amplitude value of the seismic traces involved in the calculation at the same time. When the variance volume value reaches the threshold, the variance volume value is large-scale crack data.

4. The method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs according to claim 3, characterized in that, The formula for calculating the multi-angle variance volume is: In the formula, Let xij be the variance volume value, and xij be the seismic amplitude value of the i-th trace at time j. Let be the average amplitude value of all seismic traces at time j, L be the time window length of the variance, I be the adjacent traces used to calculate the variance value at a certain point, t be the time of the calculation point, and w be the mean amplitude value of all seismic traces at time j. j- t Let be the triangular weight function within time jt, and the sum of the weighted functions is... l is the index of the triangular weight function w.

5. The method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs according to claim 1, characterized in that, The process of removing strong reflections from seismic imaging data to obtain weak signal seismic data includes: The diffracted waves are separated from the seismic imaging data using a plane wave destruction filter; The diffracted wave is subjected to strong reflection removal to obtain weak signal seismic data, which is shielded by strong reflection.

6. The method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs according to claim 5, characterized in that, Strong reflection removal of the diffracted wave includes: Dip angle estimation is performed on seismic imaging data, and median filtering is applied along the dip angle to obtain smoothed data. Subtracting slip data from seismic imaging data yields weak signal seismic data.

7. The method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs according to claim 1, characterized in that, The large-scale fracture data, the medium-scale fracture data, and the small-scale fracture data are fused at multiple resolutions to obtain multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs, including: Based on the large-scale fracture data, the mesoscale fracture data, and the small-scale fracture data, extract the large-scale fracture along-layer data, the mesoscale fracture along-layer data, and the small-scale fracture along-layer data along the seismic interpretation target layer; Based on the large-scale fracture along-layer data, the medium-scale fracture along-layer data, and the small-scale fracture along-layer data, large-scale fracture along-layer images, medium-scale fracture along-layer images, and small-scale fracture along-layer images are obtained. Gaussian images were obtained by performing Gaussian blur downsampling on large-scale, medium-scale, and small-scale crack along-layer images respectively. The Gaussian image is calculated to obtain different layers of the Gaussian image; The results of different layers of the Gaussian image are weighted and summed to obtain the multi-scale fracture characterization results of the marine-continental transitional shale gas reservoir.

8. A method for characterizing multi-scale fractures in marine-continental transitional shale gas reservoirs according to any one of claims 1-7, characterized in that, The seismic imaging data is seismic imaging data with residual noise removed.

9. A multi-scale fracture characterization device for marine-continental transitional shale gas reservoirs, characterized in that, The square device includes, The first unit is used to process seismic imaging data using multi-tilt variance volume technology to obtain large-scale crack data. The second unit is used to process seismic imaging data using ant body technology to obtain mesoscale crack data. The third unit is used to remove strong reflections from seismic imaging data to obtain weak signal seismic data. The root mean square amplitude of the weak signal seismic data is calculated to obtain the small-scale crack data; The fourth unit is used to perform multi-resolution fusion of the large-scale fracture data, the medium-scale fracture data, and the small-scale fracture data to obtain multi-scale fracture characterization information of marine-continental transitional shale gas reservoirs.

10. An electronic device comprising at least one processor and at least one memory, the memory being data-connected to the processor, wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

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